Help Center> ModelArts> DevEnviron> JupyterLab> Operation Process in JupyterLab
Updated on 2023-11-21 GMT+08:00

Operation Process in JupyterLab

ModelArts allows you to access notebook instances online using JupyterLab and develop AI models based on the PyTorch, TensorFlow, or MindSpore engines. The following figure shows the operation process.

Figure 1 Using JupyterLab to develop and debug code online
  1. Create a notebook instance.

    On the ModelArts management console, create a notebook instance with a proper AI engine. For details, see Creating a Notebook Instance.

  2. Use JupyterLab to access the notebook instance. For details, see Accessing JupyterLab.
  3. Upload training data and code files to JupyterLab. For details, see Uploading Files from a Local Path to JupyterLab.
  4. Compile and debug code in JupyterLab. For details, see JupyterLab Overview and Common Operations.
  5. In JupyterLab, call the ModelArts SDK to create a training job for in-cloud training.

    For details, see Creating a Training Job.